Notes11 - Data Warehousing Overview CS245 Notes 11 Hector Garcia-Molina Stanford University CS 245 Notes11 1 Warehousing Growing industry $8

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Data Warehousing Overview CS245 Notes 11 Hector Garcia-Molina Stanford University CS 245 1 Notes11
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CS 245 Notes11 2 Warehousing Growing industry: $8 billion in 1998 Range from desktop to huge: Walmart: 900-CPU, 2,700 disk, 23TB Teradata system Lots of buzzwords, hype ..
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CS 245 Notes11 3 Outline What is a data warehouse? Why a warehouse? Implementing a warehouse Future directions
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CS 245 Notes11 4 What is a Warehouse? Collection of diverse data subject oriented aimed at executive, decision maker often a copy of operational data with value-added data (e.g., summaries, history) integrated time-varying non-volatile more
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CS 245 Notes11 5 What is a Warehouse? Collection of tools gathering data cleansing, integrating, . .. querying, reporting, analysis data mining monitoring, administering warehouse
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CS 245 Notes11 6 Warehouse Architecture Client Client Warehouse Source Source Source Integration Metadata
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CS 245 Notes11 7 Motivating Examples Forecasting Comparing performance of units Monitoring, detecting fraud Visualization
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CS 245 Notes11 8 Why a Warehouse? Two Approaches: Query-Driven (Lazy) Warehouse (Eager) Source Source ?
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CS 245 Notes11 9 Query-Driven Approach Client Client Wrapper Wrapper Wrapper Mediator Source Source Source
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CS 245 Notes11 10 Advantages of Warehousing High query performance Queries not visible outside warehouse Local processing at sources unaffected Can operate when sources unavailable Can query data not stored in a DBMS Extra information at warehouse Modify, summarize (store aggregates) Add historical information
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CS 245 Notes11 11 Advantages of Query-Driven No need to copy data less storage no need to purchase data More up-to-date data Query needs can be unknown Only query interface needed at sources May be less draining on sources
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CS 245 Notes11 12 OLTP vs. OLAP OLTP: On Line Transaction Processing Describes processing at operational sites OLAP: On Line Analytical Processing Describes processing at warehouse
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CS 245 Notes11 13 OLTP vs. OLAP Mostly updates Many small transactions Mb-Tb of data Raw data Clerical users Up-to-date data Consistency, recoverability critical Mostly reads Queries long, complex Gb-Tb of data Summarized, consolidated data Decision-makers, analysts as users OLTP OLAP
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CS 245 Notes11 14 Data Marts Smaller warehouses Spans part of organization e.g., marketing (customers, products, sales) Do not require enterprise-wide consensus but long term integration problems?
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CS 245 Notes11 15 Data Models relations cubes Operators roll-up, drill down pivoting other
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CS 245 Notes11 16 Star customer
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Notes11 - Data Warehousing Overview CS245 Notes 11 Hector Garcia-Molina Stanford University CS 245 Notes11 1 Warehousing Growing industry $8

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